Crowd-sourced driver grading

ABSTRACT

An video analysis computing system driving analysis may include a camera associated with a first vehicle and having a viewing angle capable of capturing a video of one or more other vehicles in proximity to the first vehicle, a first memory location communicatively coupled to the camera, wherein the first memory location stores video data captured by the camera, and an evaluation module including a processor executing instructions that cause the processor to: evaluate the captured video stored in the first memory location to determine whether a driving event performed by a second vehicle has occurred, assign, in response to an identified driving event performed by the second vehicle, a driving event rating to a video showing the identified driving event, wherein the driving event rating may be calculated, at least in part, using a crowd-sourced driving event rating obtained after posting the video to a social network.

TECHNICAL FIELD

Aspects of the disclosure generally relate to providing rewards toindividuals who provide videos of driving events associated with othervehicles encountered on the road, and more specifically with rewardingcustomers who record video and rate a driving event associated withanother vehicle on the road and provide the video for presentation toothers for grading via a social network.

BACKGROUND

The collection and analysis of driving data, such as the identificationof driving behaviors and/or traffic accidents, has many applications.For example, insurance companies and financial institutions may offerrate discounts or other financial incentives to customers based on safedriving behaviors and accident-free driving records. Law enforcement orgovernment personnel may collect and analyze driving data and trafficaccident statistics to identify dangerous driving roads or times, and todetect moving violations and other unsafe driving behaviors. In othercases, driving data may be used for navigation applications, vehicletracking and monitoring applications, and on-board vehicle maintenanceapplications, among others.

Vehicle-based computer systems, such as on-board diagnostics (OBD)systems and telematics devices, may be used in automobiles and othervehicles, and may be capable of collecting various driving data andvehicle sensor data. For example, OBD systems may receive informationfrom the vehicle's on-board computers and sensors in order to monitor awide variety of information relating to the vehicle systems, such asengine RPM, emissions control, vehicle speed, throttle position,acceleration and braking rates, use of driver controls, etc. Vehiclesmay also include Global Positioning System (GPS) receivers and devicesinstalled within or operating at the vehicle configured to collectvehicle location and time data. Such vehicle-based systems may becapable of collecting driving data which may be used to perform variousdriving data analyses such as statistical driving evaluations, driverscore calculations, etc. Vehicle-based systems also may be configured todetect the occurrence of traffic accidents, for instance, using vehiclebody impact sensors and airbag deployment sensors. However, not allvehicles are equipped with systems capable of collecting, analyzing, andcommunicating driving data. Moreover, a single vehicle may be used bymultiple different drivers, and conversely, a single driver may drivemultiple different vehicles. Thus, vehicle driving data and/or accidentrecords collected by vehicle-based systems might not include the vehicleoccupants that correspond to the collected driving and accident data.

SUMMARY

The following presents a simplified summary in order to provide a basicunderstanding of some aspects of the disclosure. The summary is not anextensive overview of the disclosure. It is neither intended to identifykey or critical elements of the disclosure nor to delineate the scope ofthe disclosure. The following summary merely presents some concepts ofthe disclosure in a simplified form as a prelude to the descriptionbelow.

Aspects of the disclosure relate to methods, computer-readable media,and apparatuses for receiving telematics data (e.g., vehicle operationdata, driver data, environmental data, etc.) associated with one or morevehicles from one or more mobile devices respectively disposed withinthe one or more vehicles. Telematics data may include, for example, ageographic location of the first vehicle, a route being traversed by thefirst vehicle, driving events or maneuvers (e.g., braking, turning,accelerating) performed by the first vehicle, corresponding timestampsor timeframes, etc. In some instances, the telematics data may includesensor data from various sensors operationally coupled to the firstvehicle and configured to sense the immediate surroundings of thevehicle. A camera may be associated with the first vehicle for capturinga driving event performed by a second vehicle in proximity to the firstvehicle. An evaluation module may evaluate the captured video, with orwithout analyzing the telemetry data, to determine whether a drivingevent performed by a second vehicle has occurred and assign, in responseto an identified driving event performed by the second vehicle, a firstdriving event rating to a video showing the identified driving event.The video may then be posted to a social network to obtain acrowd-sourced driving event rating, which may then be compared to thefirst driving event rating to determine an incentive to be awarded tothe person who captured the video based on the comparison.

In some cases, a vehicle may include a camera associated with thevehicle and having a viewing angle capable of capturing a video of oneor more other vehicles in proximity to the vehicle and a telemetrydevice in communication with at least sensor capturing data associatedwith the operation of the vehicle. A first memory device may becommunicatively coupled to the camera, wherein the first memory locationstores raw video data captured by the camera. A second memory device maybe communicatively coupled to the first memory device, the second memorydevice storing a driving event video comprising a video recording of asecond vehicle performing a driving event. The vehicle may include apersonal computing device that may be detachably coupled to the vehicle,such as the mobile device 218 that may be installed in a hands-freecradle. The evaluation module may include a processor executinginstructions that cause the processor to evaluate the raw video storedin the first memory location to determine whether a driving eventperformed by a second vehicle has occurred, store at least a portion ofthe raw video in the second memory location as the driving event video,and assign a driving event rating to the driving event video showing theidentified driving event.

In some examples, a method may include capturing, by a camera associatedwith a first vehicle, a video showing a driving event performed by asecond vehicle, wherein the driving event causes a situation dangerousto other vehicles in proximity to the second vehicle, assigning adriving event rating to the video by a person who captured the video,wherein the rating quantifies a perceived danger to the other vehiclesin proximity to the second vehicle, posting, via a communicationnetwork, the video to a social network to obtain a crowd-sourced drivingevent rating for the video, and generating, by an event analyzer, acomposite driving event rating to the video based on the rating assignedby the person who captured the video and the crowd-sourced driving eventrating.

In accordance with further aspects of the present disclosure, acomputing device may determine a vehicle rating based a plurality ofdriving event ratings associated with the vehicle, where the vehiclerating may be published to provide information to drivers when apotentially dangerous vehicle is near

Other features and advantages of the disclosure will be apparent fromthe additional description provided herein.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the present invention and theadvantages thereof may be acquired by referring to the followingdescription in consideration of the accompanying drawings, in which likereference numbers indicate like features, and wherein:

FIG. 1 depicts an illustrative network environment and computing systemsthat may be used to implement aspects of the disclosure;

FIG. 2 depicts a block diagram of an illustrative driving event analysissystem, according to one or more aspects of the disclosure;

FIG. 3 depicts an illustrative block diagram of an interior space of avehicle configured to obtain a video of another vehicle performing adriving event, according to one or more aspect of the disclosure;

FIG. 4A depicts a flow diagram for an illustrative method of determininga reward for obtaining and rating a video of another vehicle performinga driving event, according to one or more aspect of the disclosure;

FIG. 4B depicts a flow diagram for an illustrative method of generatinga video and determining a rating associated with the driving eventcaptured on the video, according to one or more aspect of thedisclosure;

FIG. 5 depicts a flow diagram for an illustrative method of generatingand presenting an educational video based on the captured video of avehicle performing a driving event, according to one or more aspect ofthe disclosure; and

FIGS. 6 and 7 depict an illustrative top view of multiple vehiclestraversing a street or road, according to one or more aspects of thedisclosure.

DETAILED DESCRIPTION

In the following description of the various embodiments, reference ismade to the accompanying drawings, which form a part hereof, and inwhich is shown by way of illustration, various embodiments of thedisclosure that may be practiced. It is to be understood that otherembodiments may be utilized.

As will be appreciated by one of skill in the art upon reading thefollowing disclosure, various aspects described herein may be embodiedas a method, a computer system, or a computer program product.Accordingly, those aspects may take the form of an entirely hardwareembodiment, an entirely software embodiment or an embodiment combiningsoftware and hardware aspects. Furthermore, such aspects may take theform of a computer program product stored by one or morecomputer-readable storage media having computer-readable program code,or instructions, embodied in or on the storage media. Any suitablecomputer readable storage media may be utilized, including hard disks,CD-ROMs, optical storage devices, magnetic storage devices, and/or anycombination thereof. In addition, various signals representing data orevents as described herein may be transferred between a source and adestination in the form of electromagnetic waves traveling throughsignal-conducting media such as metal wires, optical fibers, and/orwireless transmission media (e.g., air and/or space).

FIG. 1 illustrates a block diagram of a computing system (or computingdevice) 101 in a communication system 100 that may be used according toone or more illustrative embodiments of the disclosure. The computingsystem 101 may have a processor 103 for controlling overall operation ofthe computing system 101 and its associated components, including a RAM105, a ROM 107, an input/output module 109, and one or more memorydevices 115. The computing system 101, along with one or more additionaldevices (e.g., the terminals 141, 151) may correspond to any of multiplesystems or devices, such as a driving analysis server or system,configured as described herein for receiving and analyzing vehicledriving data and calculating driver scores based on identified drivingevents.

The Input/Output (I/O) 109 may include one or more devices, such as amicrophone, keypad, touch screen, a stylus, etc., through which a userof the computing system 101 may provide input, and may also include oneor more of a speaker for providing audio output and a video displaydevice for providing textual, audiovisual and/or graphical output.Software may be stored within the one or more memory devices 115 and/orstorage to provide instructions to the processor 103 for enabling thecomputing system 101 to perform various functions. For example, the oneor more memory devices 115 may store software used by the computingsystem 101, such as an operating system 117, application programs 119,and an associated internal database 121. The processor 103 and itsassociated components may allow the computing system 101, such as adriving analysis computing system, to execute a series ofcomputer-readable instructions to receive a video showing a drivingevent of a third-party vehicle, receive grading information from thedriver providing the video, receive driving data from the vehicle,verify the driving event based on the driving data and/or the video ofthe driving event, receive image data, video data, and/or objectproximity data associated with the driving event, perform an analysis ofthe driving event based on image data, video data, and/or objectproximity data, provide the video for viewing by a plurality of viewersvia a social network, receive grading information associated with thedriving event by the plurality of users, and determine a reward or otherincentive to be provided to the individual in response to providing andgrading the video.

The computing system 101 may operate in a networked environment, such asthe communication system 100, supporting connections to one or moreremote computers, such as the terminals 141 and 151. The terminals 141and 151 may be personal computers, servers (e.g., web servers, databaseservers), or mobile communication devices (e.g., vehicle telematicsdevices, on-board vehicle computers, mobile phones, portable computingdevices, and the like), and may include some or all of the elementsdescribed above with respect to the computing system 101. The networkconnections depicted in FIG. 1 may include a local area network (LAN)125, a wide area network (WAN) 129, and/or a wireless telecommunicationsnetwork 133, but may also include other networks. When used in a LANnetworking environment, the computing system 101 may be connected to theLAN 125 through a network interface or adapter 123. When used in a WANnetworking environment, the computing system 101 may include a modem 127or other means for establishing communications over the WAN 129, such asthe network 131 (e.g., the Internet). When used in a wirelesstelecommunications network 133, the computing system 101 may include oneor more transceivers, digital signal processors, and additionalcircuitry and software for communicating with wireless computing devices(e.g., the terminals 141, 151, mobile phones, vehicle telematicsdevices, etc.) via one or more network devices 135 (e.g., basetransceiver stations) in the wireless network 133.

It will be appreciated that the network connections shown areillustrative and other means of establishing a communications linkbetween the computers may be used. The existence of any of variousnetwork protocols such as TCP/IP, Ethernet, FTP, HTTP and the like, andof various wireless communication technologies such as GSM, CDMA, WiFi,and WiMAX, is presumed, and the various computing devices and drivinganalysis system components described herein may be configured tocommunicate using any of these network protocols or technologies.

Additionally, one or more application programs 119 used by the computingsystem 101 may include computer executable instructions (e.g., drivinganalysis programs, pattern identification, video analysis programs,analysis algorithms, and/or driver score algorithms) for receiving avideo showing a driving event of a third-party vehicle, receivinggrading information from the driver providing the video, receivingdriving data from the vehicle, verifying the driving event based on thedriving data and/or the video of the driving event, receiving imagedata, video data, and/or object proximity data associated with thedriving event, performing an analysis of the driving event based onimage data, video data, and/or object proximity data, providing thevideo for viewing by a plurality of viewers via a social network,receiving grading information associated with the driving event by theplurality of users, and determining a reward or other incentive to beprovided to the individual in response to providing and grading thevideo, and performing other related functions as described herein.

As used herein, a vehicle score (e.g., a vehicle rating, a drivingrating, etc.) may refer to an evaluation of perceived driving abilities,safe driving habits, and other driver information obtained regarding athird-party vehicle encountered on the road. An event score may refer toan evaluation of perceived driving abilities, safe driving habits, andother driver information obtained regarding a driving event associatedwith the third-party vehicle encountered on the road. For example, aninsurance provider (or other business organization) may incentivize acustomer to provide and/or rate video of driving events of third partyvehicles as witnessed on the road. The video may then be published via asocial network for viewing and/or rating by a plurality of eventviewers. In some cases, the insurance provider may evaluate the drivingevents captured on the video using a driving event evaluation system,where the video footage may be analyzed, with our without additionaldriving data, to determine an event score for the driving event. In somecases, the event scores provided by the customer and/or each of theplurality of event viewers, may be aggregated, normalized or otherwiseevaluated. In some cases, the vehicle score may be assigned to thethird-party vehicle based on one or more event scores, where the eventscores may be generated by the customer witnessing one or more drivingevents, one or more viewers of the driving events via a social network,and/or the insurance provider's determined event score. In some cases,the insurance provider may use the videos, the event scores, and/or thevehicle scores to perform insurance analysis and determinations (e.g.,determine premiums and deductibles incentives, award rebates based on arating ability, determine incentives based on a quantity of videosprovided, etc.) and/or to generate educational materials (e.g., videos,quizzes, interactive presentations, etc.) identifying dangerous drivingevents and/or instructing drivers about how to avoid situations in whichsuch driving events may occur.

In some cases, the ability of the customer and/or each of the pluralityof video viewers may be assigned a reviewer score. The reviewer scoremay be used to quantify the ability of each individual (e.g., thecustomer, a viewer, the insurance provider) to provide an accuraterating of a driving event. The reviewer score may correspond to acorrelation between the viewer's rating and a rating provided by the oneor more other viewers and/or the driving event evaluation system. Forexample, a viewer may be given a higher reviewer score (e.g., 10 of 10,9 of 10, 8 of 10, 7 of 10, etc.) based on a higher correlation betweenthe viewer's rating and the other ratings of the event. Similarly, theviewer may be given a lower reviewer score (e.g., 0 of 10, 1 of 10, 2 of10, 3 of 10, etc.) based on a lower correlation between the viewer'srating and the other ratings of the event. In many cases, the insuranceprovider, such as by using the driving event evaluation system, mayperiodically calculate the reviewer score for each customer who providesvideos of driving events. In some cases, the driving event evaluationsystem may use additional information, such as telematics information,vehicle performance information, vehicle sensor information, trafficinformation, weather information, and the like when generating one ormore of the event score, the vehicle score, and/or the reviewer rating.

It should be understood that an event score, as used herein, may beassociated with an individual, group of individuals, or a vehicle. Forinstance, a family, group of friends or co-workers, or other group thatshares a vehicle, may have a single vehicle score that is shared by thegroup. Additionally, a vehicle score associated with a vehicle may haveone or more associated event scores that may be generated by one or moreprimary drivers of the vehicle and may be affected by the drivingbehavior of any the vehicle's drivers. In other examples, a vehicle maybe configured to identify different drivers, and each driver of thevehicle may have a separate event score and/or vehicle score.

FIG. 2 shows a block diagram of an illustrative driving event analysissystem 200 according to aspects of the present disclosure. Eachcomponent shown in FIG. 2 may be implemented in hardware, software, or acombination of hardware and software. Additionally, each component ofthe driving analysis system 200 may include a computing device (orsystem) having some or all of the structural components described abovefor the computing system 101. The illustrative driving event analysissystem 200 may include a plurality of vehicles 207, such as vehicle 210,in the presence of a third-party vehicle 240. For example, the vehicles207, 210 and 240 may all be near a same geographic location on aroadway. The vehicles 207 may belong to customers of a businessorganization, such as an insurance company, where drivers and/or ownersof the vehicles may be enrolled in a program to capture and provideratings of driving events encountered while operating the vehicles 207,210. In some cases, one or more devices associated with the vehicles207, 210 may be in communication with one or more other computingsystems via a wired and/or wireless communications network (e.g.,network 205). Information, such as videos of driving events, informationassociated with the vehicles 207, 210, 240, and or the like, may becommunicated from the vehicles 207, 210, 240 to one or more othercomputer systems for further analysis. For example, a video andassociated information may be communicated via the network 205 to avideo analysis computer system 250 and/or an insurance provider computersystem 260. The video analysis computer system may analyze the video andany associated information to determine a rating associated with anidentified driving event and/or the vehicle 240. The video may beprovided for viewing by other individuals (e.g., insurance providercustomers, members of the public, etc.) via one or more social networks(e.g., a private social network 254, a public social network 290, etc.).The insurance provider computer system 260 may include one or morecomputing systems and/or modules for analyzing insurance policyinformation when determining incentives and/or rewards to be awarded todrivers and/or owners who choose to capture video of driving eventsassociated with other vehicles 240. For example, the insurance providercomputer system may include an educational video database 267, a drivinganalysis computing system 280, a driving solution modeling system 264,and a vehicle operation computing system 270, an incentive module 262,an educational analysis module 268, and/or one or more user interfacescreens 266.

The driving event analysis system 200 shown in FIG. 2 may include avehicle 210, such as an automobile, motorcycle, truck, scooter, boat, orother vehicle for which a driving event data analysis may be performedand for which a driver score may be calculated. For example, the drivingevent analysis system may be used to evaluate driving events encounteredon the road (e.g., for automobiles, trucks, motorcycles, scooters,etc.), for driving events encountered on the water (e.g., for boats,personal water craft, etc.), and/or in the air (e.g., for airplanes,helicopters, etc.). The vehicle 210 may include vehicle operationsensors 212 capable of detecting and recording telematics data (e.g.,various conditions at the vehicle and operational parameters of thevehicle). For example, sensors 212 may detect and store datacorresponding to the vehicle's speed, distances driven, rates ofacceleration or braking, and specific instances of sudden acceleration,hard braking, hard turning, and swerving. Sensors 212 also may detectand store data received from the vehicle's 210 internal systems, such asimpact to the body of the vehicle, air bag deployment, headlights usage,brake light operation, door opening and closing, door locking andunlocking, cruise control usage, hazard lights usage, windshield wiperusage, horn usage, turn signal usage, seat belt usage, phone and radiousage within the vehicle, maintenance performed on the vehicle, andother data collected by the vehicle's computer systems, such as anonboard diagnostic (OBD) system.

Additional sensors 212 may detect and store the external drivingconditions, which may also be referred to herein as telematics data,(for example, external temperature, rain, snow, light levels, and sunposition for driver visibility). Sensors 212 also may detect and storetelematics data relating to moving violations and the observance oftraffic signals and signs by the vehicle 210. Additional sensors 212 maydetect and store telematics data relating to the maintenance of thevehicle 210, such as the engine status, oil level, engine coolanttemperature, odometer reading, the level of fuel in the fuel tank,engine revolutions per minute (RPMs), and/or tire pressure.

The vehicle 210 also may include one or more cameras and/or proximitysensors 214 capable of recording additional conditions inside or outsideof the vehicle 210, which may also be referred to herein as telematicsdata. For example, internal cameras 214 may detect conditions such asthe number of the passengers in the vehicle 210, and potential sourcesof driver distraction within the vehicle (e.g., pets, phone usage, andunsecured objects in the vehicle). External cameras and proximitysensors 214 may detect other nearby vehicles, traffic levels, roadconditions, traffic obstructions, animals, cyclists, pedestrians, andother conditions that may factor into a driving event data analysis. Insome cases, the vehicle 210 may include cameras and/or proximity sensors214 integrated into the mechanical systems of the vehicle, either by themanufacturer of the vehicle or by installing after-market camera and/orproximity sensor systems. In some cases, the cameras and/or proximitysensors 214 may include a mobile device associated with a driver of thevehicle 210 (e.g., a mobile phone, a global positioning system (GPS)device, a laptop, etc.) that may include one or more cameras and/orsensors that may be used for gathering information used to captureand/or to evaluate a driving event.

The operational sensors 212 and the cameras and proximity sensors 214may store data within the vehicle 210, and/or may transmit the data toone or more external computer systems (e.g., a video analysis computingsystem 250, an insurance provider computing system 260, a vehicleoperation computer system 270 and/or a driving analysis server 280). Asshown in FIG. 2, the operation sensors 212, and the cameras andproximity sensors 214, may be configured to transmit data to a vehicleoperation computer system 225 via a telematics device 216 and/or amobile device 218. In some cases, one or more of the operation sensors212 and/or the cameras and proximity sensors 214 may be configured totransmit data directly without using a telematics device 216 and/or themobile device. For example, telematics device 216 may be configured toreceive and transmit data from operational sensors 212, while one ormore cameras and proximity sensors 214 may be configured to directlytransmit data to the video analysis computing system 250 or theinsurance provider computing system 260 without using the telematicsdevice 216. Thus, telematics device 216 may be optional in certainexamples where one or more sensors or cameras 212 and 214 within thevehicle 210 may be configured to independently capture, store, andtransmit vehicle operation and driving data.

The telematics device 216 may be a computing device containing many orall of the hardware/software components as the computing system 101depicted in FIG. 1. As discussed above, the telematics device 216 mayreceive vehicle operation and driving data (e.g., telematics data) fromthe vehicle sensors 212, the cameras and/or proximity sensors 214, andmay transmit the telematics data to one or more external computersystems (e.g., a vehicle operation computer system 225 and/or a drivinganalysis server 220) over a wireless transmission network 205 (e.g., theInternet, a cellular communications network, etc.). The telematicsdevice 216 also may be configured to detect or determine additionaltypes of telematics data relating to real-time driving and the conditionof the vehicle 210. In certain embodiments, the telematics device 216may contain or may be integral with one or more of the vehicle sensors212 and cameras and proximity sensors 214 discussed above, and/or withone or more additional sensors discussed below.

In some cases, the condition and/or attention of the driver of thevehicle 210 may be relevant to whether or not the driver has correctlyidentified a driving event of the other vehicle 240. As such, thetelematics device 216 may be configured to collect telematics dataregarding the number of passengers and the types of passengers (e.g.adults, children, teenagers, pets, etc.) in the vehicle 210. Thetelematics device 216 also may be configured to collect telematics dataindicating a driver's movements or the condition of a driver. Forexample, the telematics device 216 may include or communicate withsensors that monitor a driver's movements, such as the driver's eyeposition and/or head position, etc. Additionally, the telematics device216 may collect data regarding the physical or mental state of thedriver, such as fatigue or intoxication. The condition of the driver maybe determined through the movements of the driver or through sensors,for example, sensors that detect the content of alcohol in the air orblood alcohol content of the driver, such as a breathalyzer. If thedriver's condition and/or attention is diverted from the road, thedriver may incorrectly identify or miss a driving event associated withthe other vehicle 240. This information may be used by an externalcomputing system, such as the video analysis computing system 250 and/orthe insurance provider computing system when evaluating a video of areported driving event associated with the vehicle 240.

In some cases, the location of the vehicle 210 may be useful ingenerating an event rating and/or vehicle rating to be associated withthe vehicle 240. For example, the location of the vehicle 210 may beused to obtain information about the weather and/or traffic during atime period near a time of an identified driving event of the vehicle240. In some cases, the telematics device 216, the mobile device 218 ora separate personal global positioning device may collect telematicsdata regarding the driver's route choice, whether the driver follows agiven route, and/or to classify the type of trip (e.g. commute, errand,new route, etc.). In certain embodiments, the telematics device 216 maybe configured to communicate with the sensors 212 and/or cameras and/orproximity sensors 214 to determine when and how often the vehicle 210stays in a single lane or strays into other lanes. To determine thevehicle's route, lane position, and other data, the telematics device216 and/or the mobile device may include or may receive data from one ormore of a mobile telephone, a Global Positioning System (GPS), alocational sensor positioned inside a vehicle, or a locational sensor(e.g., a roadside positional sensor) or other device remote from thevehicle 210.

The telematics device 216 and/or mobile device 218 may store theidentification information of the vehicle 210, that may include avehicle identification number, the make, model, trim (or sub-model),year, and/or engine specifications. The identification information maybe programmed into the telematics device 216 by a user or customer,determined by accessing a remote computer system, such as an insurancecompany or financial institution server, or may be determined from thevehicle itself (e.g., by accessing the vehicle's 210 computer systems).The identification information may be associated with any videocommunicated to a remote network.

The vehicle 210 also may include a personal mobile device 218 containinga number of software and hardware components. A personal mobile device218 may be located within a vehicle 210, such as a driver's orpassenger's smartphone, tablet computer, laptop computer, or otherpersonal mobile device. As used herein, a mobile device 218 “within” avehicle 210 refers to a mobile device 218 that is inside of or otherwisesecured to a moving vehicle, for instance, mobile devices 218 in thecabins of automobiles, buses, recreational vehicles, mobile devices 218traveling in open-air vehicles such as motorcycles, scooters, or boats,and mobile devices 218 in the possession of drivers or passengers ofvehicles 210. Mobile devices 220 may be, for example, smartphones orother mobile phones, personal digital assistants (PDAs), tabletcomputers, and the like, and may include some or all of the elementsdescribed above with respect to the computing system 101.

A mobile device 218 may be configured to establish communication withone or more vehicle-based devices (e.g., sensors, on-board vehiclecomputing devices, etc.) and various internal components of vehicle 210via wireless networks or wired connections (e.g., for docked devices),whereby such mobile devices 218 may have secure access to internalvehicle the sensors 212, the camera/proximity sensors 214 and othervehicle-based systems. However, in other examples, the mobile device 218might not connect to vehicle-based computing devices and internalcomponents, but may operate independently by communicating with thevehicle 210 via standard communication interfaces (e.g., short-rangecommunication systems, telematics devices 216, etc.), indirectly throughexternal networks, and servers, or might not communicate at all with thevehicle 210.

The mobile device 218 may include a network interface, which may includevarious network interface hardware (e.g., adapters, modems, wirelesstransceivers, etc.) and software components to enable the mobile device218 to communicate with external servers (e.g., the video analysiscomputing system 250), one or more vehicles such as the vehicle 210,and/or various other external computing devices. One or more specializedsoftware applications, such as a telematics data acquisition applicationor an event analyzer 230 may be stored in the memory of the mobiledevice 218, a vehicle computing system (e.g., an on-board computingsystem), or the like. In some cases, the event analyzer, or a portion ofthe event analyzer functionality may be located in a computer systemseparate from the mobile device, such as the video analysis computingsystem 250, the insurance provider computing system, and the like.Application(s) may be received via a network interface from one or moreexternal computing systems, such as the video analysis computing system250, the insurance provider computing system 260, the driving analysiscomputing system 280, the vehicle operation computing system 270, one ormore vehicles (e.g., the vehicle 210), or other application providers(e.g., a public or a private application store). Certain applicationsmight not include user interface screens, while other applications mayinclude user interface screens that support user interaction. Suchapplications may be configured to run as user-initiated applications oras background applications. The memory of mobile device 218 also mayinclude databases configured to receive and store video data, drivingevent data, vehicle data, driver or passenger data, insurance data, andthe like, associated with one or more drivers and/or vehicles. Althoughthis section describes various software application(s) as executing onmobile devices such as the mobile device 218, in various other examples,some or all of the functionality described herein may be implementedwithin the vehicle 210, via specialized hardware and/or softwareapplications within a vehicle-based system, such as software within atelematics device 216 or a vehicle control computer, etc.

In some cases, the event analyzer 230 may be configured to analyzeinformation received from one or more sources (e.g., the vehicleoperation sensors, the telematics device, the camera and/or proximitysensors 214) to determine whether a driving event associated withanother vehicle 240 has occurred. The event analyzer 230 may include aninput/output device (e.g., a keyboard, a microphone, a touchscreendisplay, an LCD display, etc.) that may be used by a driver or passengerin the vehicle 210 to provide additional information regarding aperceived driving event. In an illustrative example, the event analyzer230 may be configured to receive video input from a video cameraassociated with the vehicle 210. The camera 214 may be configured tocapture video within a field of view from the vehicle (e.g., to thefront, to the side(s), to the rear, etc.). The video may be captured andstored locally in a temporary memory location until a driving event hasbeen identified, either automatically such as by the event analyzer orin response to an input received from a user within the vehicle 210. Forinstance, a plurality of vehicles 207, 240 may be driving on a roadwayand a third-party vehicle 240 may be driving near the vehicle 210 withinthe field of view 215 of the camera 214. The camera 214 may beconfigured to take video and record continuously or nearly continuouslyto minimize a possibility that a driving event may be missed. Toconserve memory, the camera 214 may be configured to record apre-specified amount of video (e.g., about 1 minute, about 2 minutes,about 3 minutes, about 5 minutes, etc.) in a video recording memory areabefore the oldest portion is lost. In some examples, the camera 214 maybe configured to store the last minute (e.g., two minutes, threeminutes, etc.) of video. When something of interest happens, the driveror passenger of the vehicle 210 may trigger the camera to save thevideo. For example, when a driving event is recognized by the eventanalyzer 230, such as by receiving a user input or automaticallyidentifying the driving event using a video analysis algorithm, theevent analyzer 230 may determine transfer at least a portion of thevideo to be transferred to a video processing memory area for furtheranalysis. The video recording memory area and the video processingmemory area may be included in one or more of the camera 214, the mobiledevice 218 and the event analyzer 230. In other cases, the eventanalyzer 230 may communicate the video to a remote device via a network205 (e.g., a cellular communications network, a WiFi communicationsnetwork, the Internet, etc.) for additional processing. In anillustrative example, the camera 214 may communicate the stored video,in response to an identified driving event, to an external computingsystem (e.g., a cloud storage system, the insurance provider computingsystem 260, the video analysis computing system 250, etc. In some cases,the video data may be associated with other information, such as time ofday information, location information, vehicle operation information,telematics information, V2V information (e.g., information about thevehicle 240 such as vehicle identification information), weatherinformation, road condition information and the like.

Like the vehicle-based computing devices in vehicles 210, the mobiledevice 218 also may include various components configured to sense(e.g., generate or acquire) telematics data (e.g., geographic location,heading, route, linear velocity, angular velocity, acceleration,deceleration, driver data, weather data, and/or other telematics datadiscussed herein) and transmit the telematics data or other relevantdata to video analysis computing system 250 for identification ofdriving events and/or determining an event score and/or a vehicle scoreas discussed in further detail below. For example, using data frommovement sensors (e.g., 1-axis, 2-axis, or 3-axis accelerometers,compasses, speedometers, vibration sensors, gyroscopic sensors, etc.)and/or GPS receivers or other location-based services (LBS), anapplication of mobile device 218 may determine that the mobile device218 is in a moving vehicle, that a driving trip has started or stopped,has made a sudden movement such as to brake or swerve to avoid a hazardand/or that a vehicle accident has occurred. The movement sensors and/orGPS receiver or LBS component of the mobile device 218 may also be usedto determine other information such as driving speeds, routes, accidentforce, and angle of impact, and other accident characteristics andaccident-related data.

The vehicle 210 and the personal mobile device 218 may communicate witheach other via wireless networks or wired connections (e.g., for devicesphysically docked in vehicles), and each may communicate with one ormore additional vehicles 207, additional mobile computing devices,and/or a number of external computer servers (e.g., driving analysisserver 220) over one or more communication networks (e.g., cellularcommunication network, WiFi communication network, etc.). The sensordata also may be transmitted from the vehicle 210 via a telematicsdevice 216 or other network interface(s) to one or more remote computingdevices, such as one or more personal mobile devices (e.g., the mobiledevice 218) and/or external servers (e.g., the video analysis computingsystem 250). For example, the mobile computing device 218 may transmitvideo information telematics data, driver data, vehicle data (e.g.,braking, linear acceleration, angular velocity, etc.), directly to thevideo analysis computing system 250, and thus may be used in conjunctionwith or instead of telematics devices 216. Additionally, the mobilecomputing device 218 (and/or telematics device 216) may be configured toperform the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I)communications, by establishing connections and transmitting and/orreceiving telematics data to and from other nearby vehicles. Thus, themobile computing device 218 (and/or telematics device 216) may be usedin conjunction with, or instead of, a short-range communication system.In addition, the mobile computing device 218 may be used in conjunctionwith the vehicle control computers for purposes of vehicle control anddiagnostics.

An illustrative short-range communication system may be a vehicle-baseddata transmission system configured to transmit various information(e.g., an electronic vehicle identification number (VIN), driving data,vehicle data, insurance data, driver and passenger data, etc.) to othernearby vehicles, and/or to receive corresponding data from other nearbyvehicles. In some examples, communication systems may use the dedicatedshort-range communications (DSRC) protocols and standards to performwireless communications between vehicles. In the United States, 75 MHzin the 5.850-5.925 GHz band have been allocated for DSRC systems andapplications, and various other DSRC allocations have been defined inother countries and jurisdictions. However, short-range communicationsystems need not use DSRC, and may be implemented using othershort-range wireless protocols in other examples, such as WLANcommunication protocols (e.g., IEEE 802.11), Bluetooth (e.g., IEEE802.15.1), or one or more of the Communication Access for Land Mobiles(CALM) wireless communication protocols and air interfaces. The V2Vtransmissions between the short-range communication systems may be sentvia DSRC, Bluetooth, satellite, GSM infrared, IEEE 802.11, WiMAX, RFID,and/or any suitable wireless communication media, standards, andprotocols. In certain systems, short-range communication systems mayinclude specialized hardware installed in vehicles 210 (e.g.,transceivers, antennas, etc.), while in other examples the communicationsystems may be implemented using existing vehicle hardware components(e.g., radio and satellite equipment, navigation computers) and/or maybe implemented by software running on the mobile devices 218 of driversand passengers within the vehicles 210.

V2V communications also may include vehicle-to-infrastructure (V2I)communications, such as transmissions from vehicles to non-vehiclereceiving devices, for example, toll booths, rail road crossings, androad-side traffic monitoring devices. Certain V2V communication systemsmay periodically broadcast data from a vehicle 210 to any other vehicle,or other infrastructure device capable of receiving the communication,within the range of the vehicle's transmission capabilities. The rangeof V2V communications and V2I communications may depend on the wirelesscommunication standards and protocols used, the transmission/receptionhardware (e.g., transceivers, power sources, antennas), and otherfactors. Short-range V2V (and V2I) communications may range from just afew feet to many miles, and different types of telematics data andcharacteristics may be determined depending on the range of the V2Vcommunications.

Vehicle operation computer system 270 may be a computing device separatefrom the vehicle 210, containing some or all of the hardware/softwarecomponents as the computing device 101 depicted in FIG. 1. The vehicleoperation computer system 225 may be configured to receive and store thevehicle operation data discussed above from vehicle 210 and similarvehicle operation data from one or more other vehicles 207, 240. Forexample, the vehicle operation computer system 270 includes a vehicleoperation database that may be configured to store the vehicle operationdata collected from the vehicle sensors 212, proximity sensors andcameras 214, and telematics devices 216 of a plurality of vehicles. Thevehicle operation database 227 may store operational sensor data,proximity sensor data, camera data (e.g., image, audio, and/or video),location data, and/or time data associated with multiple vehicles 207,2210, and 240. In some cases, this information may be used by the videoanalysis computing system when analyzing videos of driving eventsassociated with the vehicle 240.

Data stored in the vehicle operation database may be organized in any ofseveral different manners. For example, a table in the vehicle operationdatabase may contain all of the vehicle operation data for a specificvehicle 210, similar to a vehicle event log. Other tables in the vehicleoperation database may store certain types of data for multiplevehicles. For instance, tables may store specific driving behaviors(e.g., driving speed, acceleration and braking rates, swerving,tailgating, use of seat belts, turn signals or other vehicle controls,etc.) for multiple vehicles 210 at specific locations, such as specificneighborhoods, roads, or intersections. Vehicle operation data may alsobe organized by time, so that the driving events or behaviors ofmultiple vehicles 207, 210, 240 may be stored or grouped by time (e.g.,morning, afternoon, late night, rush hour, weekends, etc.) as well aslocation.

The insurance provider computer system 260 may include a drivinganalysis computing system 280, containing some or all of thehardware/software components as the computing system 101 as depicted inFIG. 1. The driving analysis computing system 280 may include hardware,software, and network components to receive vehicle operation data fromthe vehicle operation computer system 270 and/or directly from aplurality of vehicles 207, 210 and/or a plurality of mobile devices(e.g., the mobile device 218) respectively disposed within the pluralityof vehicles. The driving analysis computing system 280 and the vehicleoperation computer system 270 may be implemented as a singleserver/system, or may be separate servers/systems. In some examples, thedriving analysis computing system 280 may be a central server configuredto receive vehicle operation data from a plurality of remotely locatedvehicle operation computer systems 270.

In an illustrative example, the driving analysis computing system 280may include a driving analysis module and a driver score calculationmodule that may be implemented in hardware and/or software configured toperform a set of specific functions within the driving analysiscomputing system 280. For example, the driving analysis module and thedriver score calculation module may include one or more driving eventanalysis/driver score calculation algorithms, driving patterndetermination and comparison algorithms, which may be executed by one ormore software applications running on generic or specialized hardwarewithin the driving analysis computing system 280. The driving analysismodule may use the vehicle operation data received from the vehicleoperation computer system 270 and/or additional image data, video data,and/or object proximity data to perform driving event analyses for thevehicle 210. The driver score calculation module may use the results ofthe driving event analysis performed by module to calculate or adjust adriver score for a driver of a vehicle based on specific driving events.Further descriptions and examples of the algorithms, functions, andanalyses that may be executed by the driving analysis server aredescribed in co-pending application “Context Based Grading” filed onMar. 25, 2016 as U.S. patent application Ser. No. 15/081,135, includedherein in its entirety. Such information regarding the driver of thevehicle 210 may be communicated and/or used by the video analysiscomputer system 250 when evaluating a driving event captured by thedriver of vehicle 210 regarding the other vehicle 240. For example, suchinformation may be used to determine whether an action performed by thedriver of the vehicle 210 may have caused by, been influenced by and/orotherwise had an effect on a particular driving event captured on videoby the camera 214.

To analyze a driving event video and/or perform other actions using thevideo and other information communicated from the vehicle 210, thedriving analysis computing system 280 and/or the video analysiscomputing system 250 may initiate communication with and/or retrievedata from one or more mobile devices, one or more vehicles 210, thevehicle operation computer system 270, and one or more additionalcomputer systems storing data that may be relevant to the driving eventanalyses, driver score calculations, and/or event rating calculations.For example, one or more traffic data storage systems, such as trafficdatabases, may store data corresponding to the amount of traffic andcertain traffic characteristics (e.g., amount of traffic, averagedriving speed, traffic speed distribution, and numbers and types ofaccidents, etc.) at various specific locations and times. The trafficdata storage systems also may store image and video data recorded bytraffic cameras various specific locations and times. One or moreweather data storage systems, such as weather databases, may storeweather data (e.g., rain, snow, sleet, hail, temperature, wind, roadconditions, visibility, etc.) at different locations and differenttimes. One or more additional driving databases/systems may storeadditional driving data from one or more different data sources orproviders which may be relevant to the driving event analyses, eventrating calculations, and/or driver score calculations. Additionaldriving databases/systems may store data regarding events such as roadhazards and traffic accidents, downed trees, power outages, roadconstruction zones, school zones, and natural disasters that may affectthe driving event analyses, event rating calculations and/or driverscore calculations performed by the driving analysis server 220 and/orthe video analysis computing system 250. In an illustrative example, thedriving analysis driving analysis computing system 280 may retrieve anduse data from these databases to analyze and evaluate the driving eventscaptured in video of the camera of the vehicles 210.

The video analysis computing system 250 may be communicatively coupledto the vehicle 210 and/or the mobile device 218 via the network 205. Forinstance, the video analysis computing system 250 may receive video, andother associated information, regarding driving events captured by thecamera 214 of the vehicle 240. This information may be stored in one ormore memory locations, such as the video database 251 and/or theanalysis database 253. In an illustrative example, the video databasemay store a driving event video linked, or otherwise associated with,other information corresponding to the driving event. For instance, thisassociated information may include a time of the event, geographiclocation information, information about the driver and/or owner of thevehicle 210 (e.g., insurance policy information, a name, anidentification number, etc.), vehicle identification information (e.g.,an electronic VIN, a full or partial image of a license plate, a full orpartial image of a driver, etc.), vehicle operation information (e.g., aspeed, an oil pressure, acceleration information, etc.), weatherinformation, traffic information, and/or the like. In some cases, theassociated information may include an identification of the drivingevent captured on video, by the driver and/or a passenger of the vehicle210. This identification may further include information aboutactivities and/or locations of the vehicles 207, 210, 240 in relation toeach other during times before and/or after the captured driving event.

The event analyzer 252 may be the same as, or different than the eventanalyzer 230 of the mobile device 218. The event analyzer 252, like theevent analyzer 230, may include one or more event analysis and/or eventrating algorithms, which may be executed by one or more softwareapplications processed by a processor of the video analysis computingsystem 250. In an illustrated example, the event analyzer may analyzethe video using video processing algorithms to identify the vehicle ofinterest (e.g., vehicle 240) in relation to one or more referencepoints, such as a fixed reference point (e.g., a horizon line, a lanemarker, a roadside object, etc.) and/or a relative reference point(e.g., a point of the vehicle 210, a location of one or more othervehicles 207, etc.). Once determined, the event analyzer 252 may processthe vehicle operation information, along with the video image, todetermine a trajectory of the vehicle 240 during the identified drivingevent. Using this trajectory, the event analyzer may compare thedetermined trajectory to trajectories associated with known drivingevents to associate the captured driving event with a particular drivingevent classification (e.g., hard braking, hard turning, excessivespeeding, swerving, improper signaling, tailgating, collisions, and/orthe like). For example, a trajectory of the vehicle 240 during a hardbraking event is different than a trajectory of the vehicle 240operating at an excessive speed or while tailgating another vehicle.This trajectory based algorithm is merely an illustrative example, andother such driving event determination algorithms may be implemented bythe event analyzer. For instance, using the video and associatedinformation, the event analyzer 252 may calculate motion information(e.g., a velocity, a position and/or an acceleration, etc.) of thevehicle 240 in relation to the vehicle 210 based on the velocity,location and/or acceleration information determined using the vehicleoperation sensors 212, along with other telematics information.

Once the event analyzer determines a driving event classification of thecaptured driving event, the video analysis computing system 250 maydetermine an event rating to be associated with the driving event by theevent analysis module 258. In some cases, the event rating may beassigned as a letter grade (e.g., A-F, etc.), a numerical grade (e.g.,1-10, 1-100, etc.), and/or the like. This event rating may be used torepresent a severity of the driving event that may be representative ofa danger posed by the vehicle 240 to its driver, other vehicles 207, 210and/or others in the vicinity (e.g., pedestrians). For example, atailgating event identified for a vehicle 240 identified as travellingat a high rate of speed in heavy traffic may receive a letter grade of Eor F (or a numerical grade of 9 or 10), while a similar tailgating eventfor the vehicle 240 identified travelling at a low rate of speed withminimal traffic may receive a different letter rating of C or D, or anumerical rating of 6 or 7. In some cases, a driving event may beidentified as a positive driving event (e.g., a correct use of a turnsignal, pulling to the side of the road for an emergency vehicle, etc.)may be identified by the driver of the vehicle 210. In such cases, thesepositive driving events may receive a letter rating of A or B, or anumerical rating of 1 or 2.

The rating analysis module 258 may utilize video information and/orother information associated with a video of a particular driving eventwhen calculating the event rating. In some cases, the driving event mayuse a numerical algorithm to calculate the event rating. For example, asample algorithm may be written as:(event rating)=a*(driving event value)+b*(vel)+c*(accel)+d*(trafficvalue)+ . . . ;where a, b, c, and d are multipliers and driving event value, vel,accel, traffic value, are numerical values associated with theinformation associated with a driving event. For example, driving eventvalue may correspond to a relative severity of the particular drivingevent, where a more severe driving event (e.g., tailgating at a highrate of speed in heavy traffic) has a higher starting value (e.g., about70) than a less severe driving event (e.g., tailgating at a lower rateof speed in minimal traffic) has a lower starting value (e.g., 35).Similarly, the values of (vel) and (accel) may be an actual velocity oracceleration value and (traffic value) may be related to a trafficdensity, where a higher traffic density corresponds to a higher number.The resulting event rating may be scaled or otherwise converted to adesired event rating that may be presented to users via one or more userinterface screens 256, viewers of a social network 254, 290 and/or usedby the insurance provider computing system 260 in generating educationalmaterial and/or determining an incentive to be awarded to the customerwho captured the video of the driving event.

In some cases, multiple vehicles 207 may capture videos, or otherinformation, of the same driving event, and/or multiple driving eventsassociated with the same vehicle. The video analysis computing system250 may be configured to aggregate event ratings associated with thesame driving event based on the videos and other informationcommunicated from the vehicles 207. For example, the ratings analysismodule 258 may compute an average, median or other combination (e.g., aweighted average based on the rating expertise of each customerproviding the videos, etc.) of the individual event ratings associatedwith each of the videos. The combined rating may then be used as theevent rating, be used to adjust the automatically generated rating, oradjust one or more equations used by the rating analysis module ingenerating an event rating. The rating analysis module may also generatea vehicle rating, by combining (e.g., averaging, a weighted combinationof event ratings, etc.) a plurality of event ratings associated with thevehicle 240. For example, the vehicle rating may be combine ratings of asame driving event obtained from multiple vehicles and/or may combineratings of two or more different driving events. In an illustrativeexample, a higher vehicle score (e.g., 9, 10, etc.) may correspond to avehicle known to be associated with a plurality of driving events and alower vehicle score may correspond to a vehicle associated with few, ifany, identified driving events.

In some cases, the rating analysis module may include a learningalgorithm that may be used to adjust the ratings and/or algorithms usedin generating the event ratings and or vehicle ratings based on acomparison of ratings provided by the submitter of the video (e.g., thedriver of the vehicle 210) and/or ratings provided by other viewers ofthe video via the social network 254, 290. In some cases, along with thevehicle ratings and the driving event ratings, the analysis database 253may also be used to store one or more algorithms used in generatingthese ratings.

Once the videos of driving events have been received and/or analyzed bythe video analysis computing system, the insurance provider may desireto post one or more of the videos to a social network 254, 290 tosolicit additional ratings from viewers of the event. In some cases, theinsurance provider post one or more videos to a private social network254 that may be under the control of the insurance provider, or abusiness partner of the insurance provider. In such a way, the insuranceprovider may have a greater control over the accuracy of the ratingsand/or control in allowing access to certain preferred individuals. Inother cases, one or more of the plurality of videos may be posted to apublic social network 290 (e.g., Twitter™, Facebook™, etc.) to allowaccess to a greater number of individuals via one or more user computingdevices 290. In some cases, the private social network 254 may utilizeone or more user interface screens 256 to present videos, solicitfeedback, and/or receive ratings information from one or moreindividuals.

The insurance provider computing system 260 may be configured togenerate one or more educational videos, or other educationalinformation, for educating drivers about dangerous driving activities.In some cases, the videos received from the vehicles 207, 210 may beused in generating such educational materials. In an example, theeducational analysis module 268 may be configured to access the videodatabase 251, with or without using the information stored in theanalysis database, to generate one or more educational videos that maythen be stored in the educational video database. In an example, theeducational analysis module 268 may identify a video based on a desiredevent rating (e.g., a higher rating, a lower rating, etc.), a desireddriving event type (e.g., hard braking, swerving, improper lane usage,hard turning, etc.), or the like. Once identified, the educationalanalysis module may identify the vehicle 240 within the video performingthe recorded driving event so that the driving solution modeling system264 may construct a model of the actions of the driver of the vehicle240 and/or to generate one or more solutions in which the driver of thevehicle 240 may have avoided the recorded driving event. In some cases,the driving solution modeling system 264 may process the video and thecalculated driver model to generate one or more alternative trajectoriesfor the vehicle 240 to travel so that the driving event may be minimizedand/or avoided. Such alternative trajectories may be overlaid on theoriginally captured video, often in response to a user input receivedvia one or more of the user interface screens 266.

The insurance provider computing system 260 may further include anincentive module 262 that may be used to generate an incentive for oneor more customers of the insurance provider who choose to participate inan incentive-based program. For example, in return for the customerinstalling hardware and/or software, the insurance provider maygenerate, or otherwise provide an incentive. The customer may beincentivized to generate and/or rate videos of other vehicles 240performing one or more driving events. These incentives may include adiscount to an insurance premium, a rebate to a previously paidinsurance premium, a predetermined amount of money per video, apredetermined number of reward points, and/or other rewards that mayprovide a reward, In some cases, the incentive module 262 may be used toadjust a determined incentive based on an ability to rate the video, anability to generate the videos, a quality of the video, and the like.

FIG. 3 shows an illustrative block diagram showing a view from aperspective of a driver or passenger of the vehicle 210. When a customerchooses to participate in a driving event ratings program, the insuranceprovider, or partner organization, may provide or otherwise suggesthardware and/or software components that may be included in a vehicle210 to enable to vehicle 210 to efficiently capture video images ofdriving events performed by another vehicle 240. For instance, thecustomer may install a camera 214 within the interior space (or exteriorspace) of the vehicle to provide the camera a sufficient view of atleast a portion of the roadway. In some cases, the camera 214 may be anaftermarket part. In some cases, the camera 214 may be a camerainstalled on the vehicle 210 by a manufacturer. In some cases, the user,or insurance provider, may provide a mounting unit 312 for mounting amobile device 218 within an interior space of the vehicle and with aview of at least a portion of the roadway. Here in FIG. 3, the camerasare shown facing forward; however other camera configurations may beused where the camera may be located to capture a portion of video outof a front window, out of a side window, and/or out a rear window of thevehicle 210. In some cases, a camera and/or a sensor (e.g., a proximitysensor, etc.) may be incorporated into the mobile device 214 or may beincorporated otherwise affixed to a portion of the vehicle, such as arear view mirror 320. As discussed above, the camera 214 may have afield of view 315, where the camera 214 may generate a video of vehicleswithin the field of view. In some cases, a vehicle driver or passengermay use an input device 330 to identify when the driver identifies adriving event. For example, the driver may use the input device, such asa physical button installed on a vehicle surface. In other cases, theinput device may be incorporated into the mobile device 218 or thevehicle computing system such as by using a touchscreen button. In somecases, the input device may include a microphone for receiving anaudible input from a user.

FIG. 4A depicts a flow diagram for an illustrative method of determininga reward for obtaining and rating a video of another vehicle performinga driving event, according to one or more aspect of the disclosure. Themethod of FIG. 4A and/or one or more steps thereof may be performed by acomputing device illustrated in FIG. 2. The method illustrated in FIG.4A and/or one or more steps thereof may be partially or fully embodied,for example, in computer-executable instructions that are stored in acomputer-readable medium, such as a non-transitory computer-readablememory. In some instances, one or more steps of FIG. 4A may be performedin a different order and/or combined. In some instances, one or moresteps of FIG. 4A may be omitted and/or otherwise not performed.

At 402, an insurance provider, or other business organization, may offerto enroll a plurality of customers into a rewards program, where therewards program may incentivize the plurality of customers to obtain andrate videos of other vehicles performing a driving event. The drivingevent may correspond to a dangerous activity performed by the driver ofthe other vehicle 240, such as hard turning, hard braking, swerving,improper lane usage, tailgating, or otherwise not driving withsufficient caution based on the conditions. At 404, if the customerenrolls, the insurance provider may allow the customer to select adesired incentive. In other cases, the insurance provider may assign aparticular incentive to the customer. The incentives may include adiscount to an insurance premium, points to be applied to anotherexisting rewards program, cash payments based on a number of videosprovided and/or the quality of the videos or ratings provided. Theincentives selected may be adjusted and/or removed based on theperformance of the customer, e.g., based on the number of videosprovided and/or the quality of the videos or ratings provided. In somecases, the incentives selected may be adjusted and/or removed based on avideo quality and/or the performance of the video once uploaded to asocial network for viewing. For example, greater weight may be given tohigher quality videos or videos having an easily identifiable drivingevent and/or based on whether how helpful the video is when determiningan underlying risk associated with the driver of the vehicle that wascaptured on the video. Further, the incentives selected may be adjustedor removed based on a number of views, where a video with a highernumber of views (e.g., a highly viewed video, a viral video, etc.) mayhave a higher incentive value than a video with a lower number of views.

At 406, once the customer has been enrolled, hardware and/or softwareapplications may be provided to the customer for use in generating thevideos, and any associated information that may be used in rating thevideo and providing an incentive to the customer. For example, theinsurance provider may specify or provide a camera 214, one or moresensors (e.g., the proximity sensors 214, the vehicle operation sensors212, etc.), and the telemetry device 216, to be installed in the vehicle210 for use in generating the videos. In some cases, one or moresoftware components (e.g., the event analyzer 230, etc.) may beincorporated with (or activated within) the vehicle computing system. Insome cases, the insurance provider may provide an input device (e.g.,the button 330, a microphone, etc.) for use by the driver or passenger,in the vehicle to trigger capture of the video and data associated withthe driving event. In some cases, the customer may use a cameraincorporated into the mobile device 218 to capture a video of thedriving event and assign an event rating to the video such as bydownloading and using the event analyzer 250 application. Here, thedriver may trigger capture of the video using a physical button (e.g.,via a wireless network such as Bluetooth), a touchscreen button on adisplay device (e.g., a display of the mobile device 218, a microphone(e.g., using voice recognition software), and/or the like. At 408, oncea video has been captured, the customer may also enter additionalinformation regarding the video, such as a rating. The event analyzer250 may associate vehicle identification information, customeridentification information, time information, location information,telemetry information, and/or the like to the video.

At 410, the accuracy of the rating the customer associates to the videomay be evaluated, such as by using the rating analysis module 258 tocompare the customer-assigned rating to a rating automatically generatedby the event analyzer 230, to ratings entered by viewers of a socialnetwork 254, 290 entered via one or more user computing device 295, or acombination of ratings. The rating analysis module 258 may utilize analgorithm that eliminates ratings outliers and then combines theremaining rating values such as by computing a weighted average of theratings. In evaluating the accuracy of the customer supplied rating, theaggregated rating may then be compared to the customer-defined eventrating, such as by comparing the difference between the aggregatedrating and the customer defined rating to a predetermined threshold. Insome cases, a computing system may generate a user interface for viewingby an individual for use in evaluating the rating provided by the user,where the user interface may allow the individual to view the video,compare the video with other videos or otherwise evaluate the videoquality and/or whether a driving event had been captured with or withoutrating analysis provided by the rating analysis module 258. At 412,based on the accuracy information, the incentive module 262 of theinsurance provider computing system 260 may be used to generate theearned incentive based on a number of videos taken within a time frame,the accuracy of the ratings assigned to the videos and whether or notthe videos may have been used by the insurance provider for educationalpurposes.

FIG. 4B depicts a flow diagram for an illustrative method of generatinga video and determining a rating associated with the driving eventcaptured on the video, according to one or more aspect of thedisclosure. The method of FIG. 4B and/or one or more steps thereof maybe performed by a computing device illustrated in FIG. 2. The methodillustrated in FIG. 4B and/or one or more steps thereof may be partiallyor fully embodied, for example, in computer-executable instructions thatare stored in a computer-readable medium, such as a non-transitorycomputer-readable memory. In some instances, one or more steps of FIG.4B may be performed in a different order and/or combined. In someinstances, one or more steps of FIG. 4B may be omitted and/or otherwisenot performed.

At 452, the camera 214 installed in the vehicle 210 may initiate captureof video data during a trip. In some cases, the user may initiate thisvideo capture. In some cases, the video capture may be automaticallyinitiated, such as by the event analyzer on the mobile device, when theevent analyzer recognizes a trip has begun. For example, the eventanalyzer may process acceleration information, velocity informationand/or location information to determine a changing geographic locationof the vehicle 210. If a driving event has not been identified, at 454,video capture continues at 452. If, at 454, a driving event has beenidentified, the customer may be prompted to provide a rating to beassociated to the driving event at 456. For example, a user may observedangerous or unsafe driving, by the vehicle 240 and indicate that adriving event is occurring, such as by using the trigger 330. Oncetriggered, the video data may be transferred from a temporary memorylocation to a different memory location along with a combination of oneor more of time information, weather information, traffic information,telemetry information, vehicle identification information, driveridentification information, and/or the like. Once the video has beencaptured, the customer may provide a rating of the driving event via auser interface device (e.g., a microphone, a user interface screen,etc.). In some cases, the customer may immediately provide a rating,such as by using the microphone. In other cases, the customer may ratethe driving event when the vehicle has stopped, or the trip hasconcluded. In such cases, the mobile device 218 or vehicle computingsystem may be configured to play back the captured video to the customervia the user interface of the mobile device 218 or vehicle computingsystem which may allow the customer to more accurately rate the drivingevent, where, in some cases, the user may utilize viewing controlsduring the evaluation (e.g., slow motion, reverse, fast forward, pause,stop, etc.).

Once rated, the video and additional information may be communicated toa memory location remote from the vehicle, such as to a cloud storagedevice and/or the video database 251. For example, a user may upload oneor more videos to the cloud storage device, or other computing interfaceto the insurance provider computing system 260 and/or the video analysiscomputing system 250. Once received, the video data may be analyzed,such as by the event analyzer 230 and/or the rating analysis module 258of the video analysis computing system 250. The video information may becommunicated in near real time (e.g., while the vehicle 210 is on atrip) to the remote memory location such as via a cellularcommunications network. At 460, the event analyzer 230 may determinewhether the current trip has ended. If not, the camera 214 may continueto capture video until the trip has ended. If so, the video analysiscomputing system, at 462, may seek input from a user regarding one ormore videos that may be published to the private social network 254and/or the public social network 290. For example, a user may bepresented with a screen listing by name or at least with an image orcopy of the videos that may be uploaded to the private social network254 and/or the public social network 290, upon verification. Oncepublished, one or more viewers may access the videos via the usercomputing devices 295 and provide a rating for each driving eventcaptured. The video analysis computing system 250 may then aggregate theratings for each video at 468.

FIG. 5 depicts a flow diagram for an illustrative method of generatingand presenting an educational video based on the captured video of avehicle performing a driving event, according to one or more aspect ofthe disclosure. The method of FIG. 5 and/or one or more steps thereofmay be performed by a computing device illustrated in FIG. 2. The methodillustrated in FIG. 5 and/or one or more steps thereof may be partiallyor fully embodied, for example, in computer-executable instructions thatare stored in a computer-readable medium, such as a non-transitorycomputer-readable memory. In some instances, one or more steps of FIG. 5may be performed in a different order and/or combined. In someinstances, one or more steps of FIG. 5 may be omitted and/or otherwisenot performed.

At 502, the one or more videos captured by the customer may be evaluatedto determine whether the driving event may be useful in educatingdrivers about dangerous and/or unsafe behavior when operating machinery.Here, once determined that the video may be useful, the educationalanalysis module 268 may be configured to analyze the video, with ourwithout the additional captured information, such as to determine atrajectory of the vehicle 240 during the driving event. At 504, thedriving solution modelling system 264 may be used to model one or moreaspects of the video so that at least one corrected trajectory may becalculated, such that the driving event may have been avoided. At 508,one or more educational videos may be generated, such as by theeducational analysis module, using the captured videos and thecalculated trajectories that may allow the user to identify ways toavoid a particular driving event. In some cases, the educationalvehicles may comprise at least a portion of a computerized rendering ofa driving event corresponding to the video, such that identificationinformation of a vehicle and/or person shown on the video may beobfuscated. Once generated, the quiz may be presented to the user forcompletion. If the user passes the quiz, the customer receive a rewardor other incentive at 410. If the user does not pass the quiz at 506,the user may be prompted to reattempt the quiz. If the user elects toretake a quiz at 508, a new quiz may be generated. at 510 and presentedto the user.

FIGS. 6 and 7 depict an illustrative top view of multiple vehiclestraversing a street or road, according to one or more aspects of thedisclosure. FIG. 6 illustrates a roadway with traffic including thevehicle 210, the vehicle 240 a performing a driving event, and othervehicles 610 a-c. Here, a plurality of vehicles may capture a samedriving event. In such cases, the ratings may be aggregated upon entryinto the computing system. For example, each car may include a camera214 having a field of view 215, 615 a-c. In some cases, the vehicles mayinclude a forward facing camera 218 (e.g., vehicle 210, 610 a, 610 b), arear facing camera (e.g., vehicle 610 c) or both As can be seen, vehicle240 a may be performing a driving event of tailgating vehicle 610 c thatmay be captured by a plurality of uninvolved vehicles, such as vehicles210, 610 a, and 610 b. In other instances, the vehicle 610 c may beconfigured to capture driving events associated with the vehicle 610 c.FIG. 7 illustrates a vehicle 240 b performing a driving event of anunsafe lane change, where vehicle may capture a video within the fieldof view 215, the vehicle 710 may capture the video of the driving eventwithin the field of view 715 a, and vehicle 710 b may capture the videoof the driving event within the field of view 715 b.

While the aspects described herein have been discussed with respect tospecific examples including various modes of carrying out aspects of thedisclosure, those skilled in the art will appreciate that there arenumerous variations and permutations of the above described systems andtechniques that fall within the spirit and scope of the invention.

The invention claimed is:
 1. A system comprising: a camera associatedwith a first vehicle and having a viewing angle capable of capturing avideo of one or more other vehicles; a first memory locationcommunicatively coupled to the camera, wherein the first memory locationstores video data captured by the camera; an evaluation module includinga processor executing instructions that cause the processor to: evaluatethe captured video stored in the first memory location to determinewhether a driving event performed by a second vehicle has occurred; andassign, in response to an identified driving event performed by thesecond vehicle, a driving event rating to a video showing the identifieddriving event; and an educational video generator communicativelycoupled to the evaluation module, the educational video generatorconfigured to: evaluate the driving event shown in the video todetermine a first trajectory of the second vehicle during the drivingevent; generate a computer visualization of at least one secondtrajectory for the second vehicle, including modelling one or moreactions of a driver of the second vehicle, wherein the second trajectorycomprises a path for the second vehicle to travel to avoid causing thedriving event; and generating an educational video by visuallyoverlaying the computer visualization of the at least one secondtrajectory to avoid performing the driving event on the captured videoshowing the second vehicle performing the driving event.
 2. The systemof claim 1 comprising: the first vehicle, wherein the camera isphysically attached to the first vehicle, and wherein generating theeducational video includes generating a computer rendering of a drivingevent corresponding to the video.
 3. The system of claim 2, wherein thecamera is physically incorporated into a mobile device and theevaluation module comprises a software application installed and runningon the mobile device.
 4. The system of claim 1, wherein a person withinthe first vehicle triggers the camera to capture the video of the secondvehicle performing the driving event; and wherein in response to thetrigger of the camera, the evaluation module captures a predeterminedtime period of video in relation to a time the capture was triggered. 5.The system of claim 4, wherein the evaluation module captures the videofor the predetermined time period before the trigger.
 6. A vehiclecomprising: a camera associated with the vehicle and having a viewingangle capable of capturing a video of one or more other vehicles inproximity to the vehicle; a telemetry device in communication with atleast one sensor configured to capture data associated with operation ofthe vehicle; a first memory device communicatively coupled to thecamera, wherein the first memory device stores raw video data capturedby the camera; a second memory device communicatively coupled to thefirst memory device, the second memory device storing a driving eventvideo comprising a video recording of a second vehicle performing adriving event; and an evaluation module including a processor executinginstructions that cause the processor to: evaluate the raw video storedin the first memory device to determine whether a driving eventperformed by a second vehicle has occurred, wherein evaluating the rawvideo includes: obtaining sensor data captured by the telemetry device;identifying the second vehicle in the raw video relative to at least oneof a fixed reference point in the video and a relative reference pointin the video; determining a trajectory of the vehicle during the drivingevent based on the raw video and the sensor data captured by thetelemetry device; and classifying the driving event by comparing thedetermined trajectory with one or more stored trajectories; store atleast a portion of the raw video in the second memory device as thedriving event video; and assign a rating to the driving event videoshowing the identified driving event.
 7. The vehicle of claim 6 whereinthe camera is physically incorporated into the vehicle and having aviewing angle capturing at least a portion of a roadway upon which thevehicle is travelling.
 8. The vehicle of claim 6, wherein the camera isphysically incorporated into a mobile device within the vehicle and theevaluation module comprises a software application installed and runningon the mobile device.
 9. The vehicle of claim 6, wherein a person withinthe vehicle triggers the camera to capture the video of the secondvehicle performing the driving event; and wherein in response to thetrigger of the camera, the evaluation module captures a predeterminedtime period of video in relation to a time the capture was triggered.10. The vehicle of claim 9, comprising an input device used by theperson within the vehicle to trigger capture a time period of the rawvideo that includes the driving event performed by the second vehicle.11. The vehicle of claim 10, wherein the input device comprises amicrophone for capturing an audio trigger spoken by the person withinthe vehicle.
 12. The vehicle of claim 9, wherein the evaluation modulecaptures the video for the predetermined time period before the trigger.13. A method comprising: capturing, by a camera associated with a firstvehicle, a video showing a driving event performed by a second vehicle,wherein the driving event causes a situation dangerous to other vehiclesin proximity to the second vehicle; assigning a driving event rating tothe video by a person who captured the video, wherein the ratingquantifies a perceived danger to the other vehicles in proximity to thesecond vehicle; posting, via a communication network, the video to asocial network to obtain a crowd-sourced driving event rating for thevideo; and generating, by an event analyzer, a composite driving eventrating to the video based on the rating assigned by the person whocaptured the video and the crowd-sourced driving event rating;determining whether the video is to be used for educational purposesbased on the composite driving event rating; and in response todetermining that the video is to be used for educational purposes:generate a computer visualization of at least one corrective trajectoryfor the second vehicle, including modelling one or more actions of adriver of the second vehicle, wherein the second trajectory comprises apath for the second vehicle to travel to avoid causing the drivingevent; and generating an educational video by visually overlaying thecomputer visualization of the at least one second trajectory to avoidperforming the driving event on the captured video showing the secondvehicle performing the driving event.
 14. The method of claim 13comprising: associating, by the event analyzer, telemetry information,sensor information, and location information with the video; evaluating,by a ratings analysis module, the video in relation to the telemetryinformation, sensor information and location information to determinewhether the rating assigned to the video is to be adjusted based, atleast in part, on the telemetry information, sensor information andlocation information.
 15. The method of claim 13, comprising: computing,by an incentives module, a difference between the driving event ratingprovided by the person who captured the video and the composite drivingevent rating; comparing the difference to a threshold; and determining,by the incentives module, an incentive to be awarded to the person forcapturing the video based, at least in part, on the comparing.
 16. Themethod of claim 15, wherein the incentives comprise at least one of adiscount to an insurance policy premium, a rebate to a previously paidinsurance premium, and a cash award based on a number of videos providedby the person within a defined time period.